SoroushVahidi/scidocs huggingface dataset:
A Unified Local and Global Model for Discourse Coherence
(2007)

We present a model for discourse coherence which combines the local entitybased approach of (Barzilay and Lapata, 2005) and the HMM-based content model of (Barzilay and Lee, 2004). Unlike the mixture model of (Soricut and Marcu, 2006), we learn local and global features jointly, providing a better theoretical explanation of how they are useful. As the local component of our model we adapt (Barzilay and Lapata, 2005) by relaxing independence assumptions so that it is effective when estimated generatively. Our model performs the ordering task competitively with (Soricut and Marcu, 2006), and significantly better than either of the models it is based on.
A knowledge-based table recognition method for Chinese bank statement images
(2016)

Automatic processing of large volume scanned Chinese bank statements is a urgent demand recently. Conventional methods can not well handle the following challenges of this problem: various layout styles, noises, and especially requirement of fast speed for large Chinese character set. This paper proposes a knowledge based table recognition method to meet fast speed requirement with good accuracy. Two kinds of knowledge are utilized to accelerate the identification of digit columns and the cell recognition: i) geometric knowledge about column alignment and quasi equal digit width, and ii) semantic knowledge about prior format based on the results from an optical character recognition (OCR) engine of digits. Experimental results on a real dataset show the effectiveness of our method.
Artificial Neural Network Method for Solution of Boundary Value Problems With Exact Satisfaction of Arbitrary Boundary Conditions
(2009)

A method for solving boundary value problems (BVPs) is introduced using artificial neural networks (ANNs) for irregular domain boundaries with mixed Dirichlet/Neumann boundary conditions (BCs). The approximate ANN solution automatically satisfies BCs at all stages of training, including before training commences. This method is simpler than other ANN methods for solving BVPs due to its unconstrained nature and because automatic satisfaction of Dirichlet BCs provides a good starting approximate solution for significant portions of the domain. Automatic satisfaction of BCs is accomplished by the introduction of an innovative length factor. Several examples of BVP solution are presented for both linear and nonlinear differential equations in two and three dimensions. Error norms in the approximate solution on the order of 10-4 to 10-5 are reported for all example problems.
Promoting tourism destinations : A strategic marketing approach
(2007)

Introduction This paper outlines the main topics of a report prepared for the Tourism Promotion Committee (TPC) in Heraklion District, Crete. This body is responsible for coordinating marketing activities and promoting its area. Its membership is composed of the main public and private sector organizations involved in providing tourism services in Crete. The report was compiled for TPC by the first author, who has been closely involved in the development of tourism marketing and planning on Crete for over ten years. It was commissioned with the aim of improving the destination’s marketing effectiveness and efficiency. The task assigned was to provide a report (i) reviewing the marketing activities undertaken by the TPC; (ii) providing the appropriate approach to be adopted and implemented in promoting Heraklion as tourism destination; and (iii) giving a set of recommendations for key areas requiring improvement. Marios D. Soteriades and Vasiliki A. Avgeli
Zoomorphic design
(2015)

Zoomorphic shapes are man-made shapes that possess the form or appearance of an animal. They have desirable aesthetic properties, but are difficult to create using conventional modeling tools. We present a method for creating zoomorphic shapes by merging a man-made shape and an animal shape. To identify a pair of shapes that are suitable for merging, we use an efficient graph kernel based technique. We formulate the merging process as a continuous optimization problem where the two shapes are deformed jointly to minimize an energy function combining several design factors. The modeler can adjust the weighting between these factors to attain high-level control over the final shape produced. A novel technique ensures that the zoomorphic shape does not violate the design restrictions of the man-made shape. We demonstrate the versatility and effectiveness of our approach by generating a wide variety of zoomorphic shapes.
A New Iterative Secret Key Cryptosystem Based on Reversible and Irreversible Cellular Automata
(2016)

Many cryptosystems have been released to secure electronic data on internet. Some data are very critical to be transmitted as plaintext. Thus, to ensure the data confidentiality and integrity, a list of cryptosystems have been elaborated. The most important ones are divided into two categories: symmetric algorithms encrypting and decrypting data in blocks using a single secret key; and asymmetric algorithms using public keys to cipher texts and secret keys to reconstruct plaintexts. The of the present work is the design and implement a new secret key cryptosystem encrypting and decrypting data in blocks according to a number of iterations. Each plaintext block is encrypted using cellular automata and a list of sub keys deduced from a secret key through cellular automata. To demonstrate the feasibility, the proposed scheme is compared with AES algorithm, the well-known symmetric block cipher. We prove that our algorithm resists against statistical attacks and it is faster than AES-256 achieving good confusion and diffusion tests.
Differential Cryptanalysis of Feal and N-Hash
(1991)

In 1,2] we introduced the notion of diierential cryptanalysis and described its application to DESS11] and several of its variants. In this paper we show the applicability of diierential cryptanalysis to the Feal family of encryption algorithms and to the N-Hash hash function. In addition, we show how to transform diierential cryptanalytic chosen plaintext attacks into known plaintext attacks.
A new kind of science
(2002)

The distinctive idea is easy to state, though it needs some examples to appreciate. It is that simple rules can generate complex very complex outcomes when they are repeatedly applied. Isolated examples of this phenomenon have been known for centuries. For example, the number p has a simple definition the ratio of a circle's circumference to its diameter and there is a quite simple formula to calculate its digits. The result begins: 3.14159265358979323846264338327950288419716939937510582097494459230781640 6286208998628034825342117068...
Fixed-point algorithms for learning determinantal point processes
(2015)

Determinantal point processes (DPPs) offer an elegant tool for encoding probabilities over subsets of a ground set. Discrete DPPs are parametrized by a positive semidefinite matrix (called the DPP kernel), and estimating this kernel is key to learning DPPs from observed data. We consider the task of learning the DPP kernel, and develop for it a surprisingly simple yet effective new algorithm. Our algorithm offers the following benefits over previous approaches: (a) it is much simpler; (b) it yields equally good and sometimes even better local maxima; and (c) it runs an order of magnitude faster on large problems. We present experimental results on both real and simulated data to illustrate the numerical performance of our technique.
An Automated Approach for Digital Forensic Analysis of Heterogeneous Big Data
(2016)

The major challenges with big data examination and analysis are volume, complex interdependence across content, and heterogeneity. The examination and analysis phases are considered essential to a digital forensics process. However, traditional techniques for the forensic investigation use one or more forensic tools to examine and analyse each resource. In addition, when multiple resources are included in one case, there is an inability to cross-correlate findings which often leads to inefficiencies in processing and identifying evidence. Furthermore, most current forensics tools cannot cope with large volumes of data. This paper develops a novel framework for digital forensic analysis of heterogeneous big data. The framework mainly focuses upon the investigations of three core issues: data volume, heterogeneous data and the investigators cognitive load in understanding the relationships between artefacts. The proposed approach focuses upon the use of metadata to solve the data volume problem, semantic web ontologies to solve the heterogeneous data sources and artificial intelligence models to support the automated identification and correlation of artefacts to reduce the burden placed upon the investigator to understand the nature and relationship of the artefacts.
Application of Katharine Kolkaba Comfort theory to nursing care of patient
(2017)

aring is in practice since existence but caring as profession named Nursing was scientifically Coined by the founder of modern nursing who in her writings “what it is and what it is not”declared the boundaries along with its Constitutional elements. Those elements with appropriate association not only revealed the nature of caring dogma it also shows that it is doing something base on thinking something or in simple words this is practice rely on theory. According to McCrae, (2011) For the sake of assuming valuable status ofprofession in society nursing struggle to legitimate its position by generation and application of theory. Nursing literature is rich regarding theory practice association. although constant body of argument, counter argument and lack of agreed conclusion regarding nursing theory creates a bit confusion among nurses but ideally nursing theory should set the code of every day practice of nurses(Giltinane, 2013) as lack of a valued unique contribution nurses make to health care based on a specialized body of knowledge will portrayed nursing role as subordinate to doctor (Mccrae, 2011) Eminent nurses’ theorist, scientist, Researchers, Clinicians, Educators and intellectual intelligentsia aid evidence to different perspectives of theory practice link. Some unanimous convincing narratives argue that the relationship is reciprocal and according to (Mckenna, 2005) Nursing theory takes its origin from practice, than reverse to practice for testing and at the end become set to guide the practice.
Applying autonomous sensor systems in logistics — Combining sensor networks , RFIDs and software agents
(2005)

New sensor, communication and software technologies are used to broaden the facilities of tracing and tracing systems for food transports. n embedded assessing unit detects from sensor data collected by a wireless network potential risks for the freight quality. The estimation of he current maturing state of agricultural products will be supported by measurements of the gaseous hormone ethylene as an indicator for the ipening processes. A miniaturized high-resolution gas chromatography is under construction. The system autonomously configures itself to a roduct specific supervision task based on data scanned by an RFID reader during freight loading. Mobile software agents accompany the freight long the supply chain. They pre-process the vast sensor data and submit only substantial changes to the freight owner. 2006 Elsevier B.V. All rights reserved.
Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey
(2016)

This paper provides a state-of-the-art literature review on economic analysis and pricing models for data collection and wireless communication in Internet of Things (IoT). Wireless sensor networks (WSNs) are the main components of IoT which collect data from the environment and transmit the data to the sink nodes. For long service time and low maintenance cost, WSNs require adaptive and robust designs to address many issues, e.g., data collection, topology formation, packet forwarding, resource and power optimization, coverage optimization, efficient task allocation, and security. For these issues, sensors have to make optimal decisions from current capabilities and available strategies to achieve desirable goals. This paper reviews numerous applications of the economic and pricing models, known as intelligent rational decision-making methods, to develop adaptive algorithms and protocols for WSNs. Besides, we survey a variety of pricing strategies in providing incentives for phone users in crowdsensing applications to contribute their sensing data. Furthermore, we consider the use of some pricing models in machine-to-machine (M2M) communication. Finally, we highlight some important open research issues as well as future research directions of applying economic and pricing models to IoT.
Near-Duplicates Detection and Elimination Based on Web Provenance for Effective Web Search
(2012)

Users of World Wide Web utilize search engines for information retrieval in web as search engines play a vital role in finding information on the web. However, the performance of a web search is greatly affected by flooding of search results with information that is redundant in nature i.e., existence of nearduplicates. Such near-duplicates holdup the other promising results to the users. Many of these near-duplicates are from distrusted websites and/or authors who host information on web. Such nearduplicates may be eliminated by means of Provenance. Thus, this paper proposes a novel approach to identify such near-duplicates based on provenance. In this approach a provenance model has been built using web pages which are the search results returned by existing search engine. The proposed model combines both content based and trust based factors for classifying the results as original or near-duplicates. Keywords— Web search, Near-duplicates, Provenance, Semantics,
Schemaless NoSQL Data Stores - Object-NoSQL Mappers to the Rescue?
(2015)

NoSQL data stores are becoming increasingly popular in application development. These systems are attractive for developers due to their ability to handle large volumes of data, as well as data with a high degree of structural variety. Typically, NoSQL data stores are accessed programmatically. Due to the imminent lack of standardized query languages, building applications against the native interfaces of NoSQL data stores creates an unfortunate technical lock-in. To re-gain platform independence, developers turn to object mapper libraries as an additional level of abstraction when accessing NoSQL data stores. The current market for Java object mappers that support NoSQL data stores is still volatile, with commercial and open source products competing for adoption. In this paper, we give an overview on the state-of-the-art in Object-Relational Mappers that can handle also NoSQL data stores, as well as dedicated Object-NoSQL Mappers. We are able to show that choosing the right object mapper library is a strategic decision with far reaching consequences: Current mappers diverge in the NoSQL data stores that they support, in their features, their robustness, their truthfulness to the documentation and query standards, and ultimately, in the runtime overhead that they introduce. Especially in web development, runtime overhead is a crucial aspect contributing to the application latency, and ultimately, the user experience. By shedding light on the current market, we intend to provide software architects with the necessary information to make informed decisions.
Efficient Image Dehazing with Boundary Constraint and Contextual Regularization
(2013)

Images captured in foggy weather conditions often suffer from bad visibility. In this paper, we propose an efficient regularization method to remove hazes from a single input image. Our method benefits much from an exploration on the inherent boundary constraint on the transmission function. This constraint, combined with a weighted L1-norm based contextual regularization, is modeled into an optimization problem to estimate the unknown scene transmission. A quite efficient algorithm based on variable splitting is also presented to solve the problem. The proposed method requires only a few general assumptions and can restore a high-quality haze-free image with faithful colors and fine image details. Experimental results on a variety of haze images demonstrate the effectiveness and efficiency of the proposed method.
Trust in Online Shopping: The Korean Student Experience
(2008)

E-commerce has become an important part of business. In South Korea, the market size of online shopping malls was 13,460 billion Korean Won in 2006, and this figure keeps growing. Thus, gaining loyal customers has become a rising concern. In this study, we adopted Lewicki and Bunker's three different types of trust, namely, calculus-based trust, knowledge-based trust, and identification-based trust, in order to investigate their hierarchical relationships in e-commerce and their impacts on customer satisfaction and loyalty. A total of 104 responses from university students were analyzed to test the proposed model and its hypotheses using PLS. The results showed that hierarchical relationships between different types of trust exist in the online environment, and among them, knowledge-based trust has the strongest impact on customer satisfaction. This finding implied that practitioners should focus on developing an appropriate online strategy in terms of how to build up trust-based relationships with online customers.
Music-based respiratory biofeedback in visually-demanding tasks
(2015)

Biofeedback tools generally use visualizations to display physiological information to the user. As such, these tools are incompatible with visually demanding tasks such as driving. While auditory or haptic biofeedback may be used in these cases, the additional sensory channels can increase workload or act as a nuisance to the user. A number of studies, however, have shown that music can improve mood and concentration, while also reduce aggression and boredom. Here, we propose an intervention that combines the benefits of biofeedback and music to help users regulate their stress response while performing a visual task (driving a car simulator). Our approach encourages slow breathing by adjusting the quality of the music in response to the user’s breathing rate. We evaluate the intervention on a design with music and auditory biofeedback as independent variables. Our results indicate that our music-biofeedback intervention leads to lower arousal (reduced electrodermal activity and increased heart rate variability) than music alone, auditory biofeedback alone and a control condition.
Graph databases: A survey
(2015)

In the era of big data, data analytics, business intelligence database management plays a vital role from technical business management and research point of view. Over many decades, database management has been a topic of active research. There are different type of database management system have been proposed over a period of time but Relational Database Management System (RDBMS) is the one which has been most popularly used in academic research as well as industrial setup[1]. In recent years, graph databases regained interest among the researchers for certain obvious reasons. One of the most important reasons for such an interest in a graph database is because of the inherent property of graphs as a graph structure. Graphs are present everywhere in the data structure, which represents the strong connectivity within the data. Most of the graph database models are defined in which data-structure for schema and instances are modeled as graph or generalization of a graph. In such graph database models, data manipulations are expressed by graph-oriented operations and type constructors [9]. Now days, most of the real world applications can be modeled as a graph and one of the best real world examples is social or biological network. This paper gives an overview of the different type of graph databases, applications, and comparison between their models based on some properties.
Fundamentals of Wearable Computers and Augmented Reality, Second Edition
(2016)

The best ebooks about Fundamentals Of Wearable Computers And Augmented Reality Second Edition that you can get for free here by download this Fundamentals Of Wearable Computers And Augmented Reality Second Edition and save to your desktop. This ebooks is under topic such as fundamentals of wearable computers and augmented reality fundamentals of wearable computers and augmented reality fundamentals of wearable computers and augmented reality fundamentals of wearable computers and augmented reality fundamentals of wearable computers and augmented reality fundamentals of wearable computers and augmented reality fundamentals of wearable computers and augmented reality 11 location-based mixed and augmented reality storytelling fundamentals of wearable computers and augmented reality forum book review mit press journals the vietnam war revised 2nd edition ebook | slangsurfing dicom to 3d holograms: use case for augmented reality in pensees de j j rousseau citoyen de geneve v1 2 1785 ebook click here to access this book : free download amendment xivequal protection constitutional amendments solutions manual to fundamentals of engineering document about distant mirrors america as a foreign regeneration of peasants slangsurfing the cell ebook | esmajorelojes il buddhismo contemporaneo italian edition ebook | slanggeek proceedings of a court of inquiryconvened at the navy answer coming soonmore blog postings on arts letters the travel and tropical medicine manual 4e ebook fundamentals of sql server 2012 replication
The State of Public Infrastructure-as-a-Service Cloud Security
(2015)

The public Infrastructure-as-a-Service (IaaS) cloud industry has reached a critical mass in the past few years, with many cloud service providers fielding competing services. Despite the competition, we find some of the security mechanisms offered by the services to be similar, indicating that the cloud industry has established a number of “best-practices,” while other security mechanisms vary widely, indicating that there is also still room for innovation and experimentation. We investigate these differences and possible underlying reasons for it. We also contrast the security mechanisms offered by public IaaS cloud offerings and with security mechanisms proposed by academia over the same period. Finally, we speculate on how industry and academia might work together to solve the pressing security problems in public IaaS clouds going forward.